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RunKeeper VS Matplotlib

Compare RunKeeper VS Matplotlib and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

RunKeeper logo RunKeeper

Join the community of over 45 million runners who make every run amazing with Runkeeper. Track your workouts and reach your fitness goals!

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • RunKeeper Landing page
    Landing page //
    2023-03-23
  • Matplotlib Landing page
    Landing page //
    2023-06-14

RunKeeper features and specs

  • Comprehensive Tracking
    RunKeeper offers detailed tracking of various activities including running, walking, cycling, and other cardio exercises using GPS.
  • User-Friendly Interface
    The app features an easy-to-navigate interface, making it accessible for users of all technical skill levels.
  • Personalized Fitness Plans
    RunKeeper provides personalized fitness plans and goals based on user input and activity history.
  • Social Features
    Users can share their progress with friends, participate in challenges, and encourage each other to stay motivated.
  • Integration Capabilities
    The app integrates seamlessly with other popular fitness devices and apps, including Fitbit, MyFitnessPal, and Apple Health.
  • Audio Cues
    RunKeeper provides audio cues during workouts to keep users informed about their pace, distance, and time.

Possible disadvantages of RunKeeper

  • Premium Features
    Some of the more advanced features and detailed analytics are only available through a paid subscription.
  • Battery Consumption
    Continual use of GPS tracking can significantly drain the battery life of a mobile device.
  • App Stability
    Some users report occasional bugs and crashes, particularly after updates.
  • Limited Indoor Tracking
    The app does not track indoor activities, such as treadmill running, as accurately as outdoor activities.
  • Data Privacy
    Users need to be cautious about their data privacy, as the app collects a significant amount of personal fitness data.

Matplotlib features and specs

  • Versatility
    Matplotlib can generate a wide variety of plots, ranging from simple line plots to complex 3D plots. This versatility makes it a go-to library for many scientific and technical visualizations.
  • Customization
    It offers extensive customization options for virtually every element of a plot, including colors, labels, line styles, and more, allowing users to tailor plots to meet specific needs.
  • Integrations
    Matplotlib integrates well with other Python libraries such as NumPy, Pandas, and SciPy, making it easier to plot data directly from these sources.
  • Community and Documentation
    It has a large, active community and comprehensive documentation that includes tutorials, examples, and detailed references, which can help users solve problems and improve their plot-making skills.
  • Interactivity
    Matplotlib supports interactive plots, which can be embedded in Jupyter notebooks and GUIs, allowing for dynamic data exploration and presentation.
  • Publication-Quality
    The library is capable of producing high-quality, publication-ready graphics that meet the stringent requirements of academic journals and professional presentations.

Possible disadvantages of Matplotlib

  • Complexity
    While Matplotlib offers extensive customization, it can be complex and sometimes unintuitive for beginners, requiring a steep learning curve to master all its functionality.
  • Performance
    Rendering a large number of plots or handling very large datasets can be slow, making Matplotlib less suitable for real-time data visualization.
  • Modern Aesthetics
    Out-of-the-box plots from Matplotlib can look somewhat dated compared to those from newer plotting libraries like Seaborn or Plotly, requiring additional customization to achieve a modern look.
  • 3D Plots
    Although Matplotlib supports 3D plotting, its capabilities are relatively limited and less sophisticated compared to specialized 3D plotting libraries.
  • Size and Structure
    The package is relatively large and can be slow to import. Its extensive structure can make finding specific functions and understanding the overall architecture challenging.

Analysis of RunKeeper

Overall verdict

  • Overall, RunKeeper is a great tool for both beginners and advanced users who want to keep track of their fitness activities. Its combination of features, ease of use, and ability to personalize workouts make it a popular choice among fitness enthusiasts.

Why this product is good

  • RunKeeper is widely considered a good fitness app due to its user-friendly interface, extensive features for tracking various physical activities such as running, cycling, and walking, and its ability to sync with other fitness devices and apps. It provides detailed insights into your performance, goals, and progress over time, which can be motivating for many users.

Recommended for

    RunKeeper is recommended for individuals who are looking for a reliable app to track their running and other cardio workouts. It is suitable for those who want to set personal fitness goals, monitor their progress, and need some motivation through challenges and community support. Both casual exercisers and serious athletes can benefit from the app.

Analysis of Matplotlib

Overall verdict

  • Yes, Matplotlib is a good library for data visualization, particularly for users who require a versatile and powerful plotting solution in Python.

Why this product is good

  • Matplotlib is highly regarded due to its extensive customization options, versatility in creating a wide range of static, animated, and interactive plots, and its large user community and support. It integrates well with other scientific libraries in Python, making it a staple for data visualization. The library is also open-source and frequently updated, ensuring it remains a reliable choice for users.

Recommended for

  • Data scientists and analysts needing to create detailed, customized visual representations of their data.
  • Researchers and engineers looking for a comprehensive plotting library that supports scientific and engineering formats.
  • Python developers who require integration with other scientific computing libraries like NumPy and Pandas.

RunKeeper videos

+ Add

Runkeeper App Review

More videos:

  • Review - The BEST iPhone Running Apps! - RunKeeper Pro and Nike+ GPS Review - Apps to Help You Train!
  • Review - 10k Training | Intervals with Runkeeper

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to RunKeeper and Matplotlib)

RunKeeper

Matplotlib

Health And Fitness
100 100%
Health And Fitness
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Sport & Health
100 100%
Sport & Health
0% 0
Technical Computing
0 0%
Technical Computing
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare RunKeeper and Matplotlib

RunKeeper Reviews

Top 10 App Like Strava. If you want to build an app likeโ€ฆ | by Vikas Agrawal | Medium
RunKeeper offers a personalized running experience with training plans and audio cues. Itโ€™s an excellent choice for runners looking to improve their performance and achieve new milestones.
Source: medium.com
10 Best Strava Alternatives Apps (2023) โ€“ Apps Like Strava
On top of the list, we are presenting the Runkeeper powered by the famous sports brand ASICS. The handy app can count the distance you covered, the pace, and the calories burnt. Also, provide audio updates while you run.
Source: techdator.net
14 Best Strava Alternatives and Similar Apps
Many are wondering why people compare RunKeeper vs. Strava. Why is it? Both are popular with runners, but RunKeeper is chosen as the best because of its flexible running logs where you could add your runs manually.
Source: www.regendus.com
10 best fitness tracker apps for Android
Runkeeper is a fitness tracker app for runners. It tracks things like distance, pace, and frequency of your runs. The app has support for Wear OS devices as well as other apps like MyFitnessPal. It works pretty well. You basically hit the go button and then start running. The app does the rest. It also includes a stopwatch mode for things like indoor cardio via treadmill. It...
Source: www.androidauthority.com

Matplotlib Reviews

25 Python Frameworks to Master
Matplotlib is a widely used tool for data visualization in Python. It provides an object-oriented API for embedding plots into applications.
Source: kinsta.com
5 Best Python Libraries For Data Visualization in 2023
You can use this library for multiple purposes such as generating plots, bar charts, histograms, power spectra, stemplots, pie charts, and more. The best thing about Matplotlib is you just have to write a few lines of code and it handles the rest by itself. Metaplotilib focuses on static images for publication along with interactive figures using toolkits like Qt and GTK.
Source: www.technotification.com
15 data science tools to consider using in 2021
Matplotlib is an open source Python plotting library that's used to read, import and visualize data in analytics applications. Data scientists and other users can create static, animated and interactive data visualizations with Matplotlib, using it in Python scripts, the Python and IPython shells, Jupyter Notebook, web application servers and various GUI toolkits.
Source: searchbusinessanalytics.techtarget.com
Top Python Libraries For Image Processing In 2021
Matplotlib is primarily used for 2D visualizations such as scatter plots, bar graphs, histograms, and many more, but we can also use it for image processing. It is effective to get information out of an image. It doesnโ€™t support all file formats.
Source: www.analyticsvidhya.com
Top 8 Python Libraries for Data Visualization
Matplotlib is a data visualization library and 2-D plotting library of Python It was initially released in 2003 and it is the most popular and widely-used plotting library in the Python community. It comes with an interactive environment across multiple platforms. Matplotlib can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application...
Source: www.geeksforgeeks.org

Social recommendations and mentions

Based on our record, Matplotlib seems to be a lot more popular than RunKeeper. While we know about 114 links to Matplotlib, we've tracked only 1 mention of RunKeeper. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

RunKeeper mentions (1)

  • Top 3 Toronto Summer Running Tips
    Runkeeper: Asicsโ€™ fitness tracker is available for iOS and Android and does just about everything in terms of route planning, activity tracking, and metrics. Source: over 4 years ago

Matplotlib mentions (114)

  • The soul file
    In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ€” the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 4 months ago
  • How to Analyze CSV Files with Python and Pandas
    Numbers are useful, but sometimes itโ€™s easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 7 months ago
  • libmalloc, jemalloc, tcmalloc, mimalloc - Exploring Different Memory Allocators
    We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 8 months ago
  • Building an AI Scoring Agent: Step-By-Step
    NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 9 months ago
  • Top 5 GitHub Repositories for Data Science in 2026
    The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโ€ฆ. - Source: dev.to / 10 months ago
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What are some alternatives?

When comparing RunKeeper and Matplotlib, you can also consider the following products

Strava - The #1 app for runners and cyclists

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Runtastic - Runtastic offers a series of fitness apps that can be used to track your running, walking, hiking, and cycling, as well as many other fitness routines. Read more about Runtastic.

NumPy - NumPy is the fundamental package for scientific computing with Python

MyFitnessPal - Track the number of calories that you consume each day with MyFitnessPal. The app also lets you create a diet and track the exercise that you complete each day whether it's walking, running or some other type of program.

Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.

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